# classIfication
import pymysql
import pandas as pd
import datetime

class MysqlUtils(object):
    def __init__(self):
        self.conn = pymysql.connect(
            host='127.0.0.1',
            user='root',
            passwd="root",
            port=3306,
            db="tushare",
            charset= "utf8"
        )
class classIfication(object):
    def __init__(self):
        pass

    def get_fina_indicator(self,conn):
        """获取财务数据"""
        cursor = conn.cursor(cursor=pymysql.cursor.DictCursor)

        sql = "SELECT ts_code, ann_data, eps, total_revenue_ps, undist_ps, gross_margin, fcff, fcfe, tangible_asset, bps, grossprofit_maigin, npta From financial_data WHERE ann_date >='2023-01-01' and ann_date < '2024-0101'"
        
        cursor.execute(sql)
        ret = cursor.fetchall()

        df = pd.DataFrame(ret)
        #数据清洗
        df = df.dropna(subset=['eps','total_revenue_ps', 'undist_ps', 'gross_margin', 'fcff, fcfe', 'tangible_asset', 'bps', 'grossprofit_maigin', 'npta'])
        #重建索引
        df1 = df1.reset_index(drop=False)

        return df1

    def get_daily(self , conn, df):
        cursor = conn.cursor(cursor=pymysql.cursors.DictCursor)
        new_list = []

        for i in range (len(df['ts_code'])):
            ann_date= df['ann_date'][i].strftime('%Y%m%d')
            sql= "select trade_data,closes from date_1 where ts_code = \'"+df['ts_code'][i] +" \' and trade_date > Date(\'"+ ann_date +"\') order by trade_date asc limit 20"
          
            cursor.execute(sql)
            ret = cursor.fetchall()
            df1 = pd.DataFrame(ret)
            print(i)

            try:
                if  len(df) > 0:
                    max_close = df1['closes'].max()
                    min_close = df1['closes'].min()
                    the_close = df1['closes'].iloc[i]

                    new_list.append({
                        'ts_code': df['ts_code'][i],
                        'ann_date': df['ann_date'][i],
                        'max_close': max_close,
                        'min_close': min_close,
                        'the_close': the_close,
                        'eps': df['eps'][i],
                        'total_revenue_ps': df['total_revenue_ps'][i],

                        'undist_profit_ps': df['undist_profit_ps'][i],
                        'gross_margin': df['gross_margin'][i],
                        'fcff': df['fcff'][i],
                        'fcfe': df['fcfe'][i],
                        'tangible_asset': df['tangible_asset'][i],
                        'bps': df['bps'][i],
                        'grossprofit_margin': df['grossprofit_margin'][i],
                        'npta': df['npta'][i],
                        
                    })
            except Exception as e:
                print(e)
            df2 = pd.DataFrame(new_list)
            df2.to_csv('daily.csv', index=False)
if __name__ == '__main__' :
    mu = MysqlUtils()
    ci = classIfication()
    df =  ci.get_final_indicator(mu.conn)
    ci.et_daily(mu.conn, df)           
    